IT professionals are busy people these days. They’ve seen their responsibilities mushroom as they scramble to provide remote employees with access to corporate resources and manage new cybersecurity risks that home offices create.
With half a million unfilled IT jobs in the U.S. alone, many IT departments are short on time to shoulder greater volumes of tasks. Some are turning to machine learning (ML) for help, an alternative now more broadly attainable thanks to emerging low-code and no-code applications.
Nutanix, for example, is using these tools to bridge the gap between its IT processes and ML algorithms, said Wendy M. Pfeiffer, Nutanix CIO, who led her company’s transformation to a hybrid multicloud IT operation. While plenty of IT tasks could benefit from ML, work can only be offloaded to ML for automation once it’s well understood and documented, she explained. This has been a sticking point with ML technology adoption, she said.
Traditionally, once work processes are documented, a developer writes a script linking them to the ML algorithms. But this procedure requires special development expertise that’s not always in abundant supply.
New low-code/no-code tools, however, don’t require developers for this function, which Pfeiffer expects to accelerate ML adoption. Nutanix IT is already using one such tool, Workato, which enables the department to use predictive analytics and ML software to accomplish an escalating volume of work.
“Three years ago, 11% of our work was handled autonomously; today, that number is 86%,” she said.
Though her department has long worked toward automation, she explained, it was “these steps and modern technology that have made the difference” in turning the corner with it.
Nutanix IT Automation Processes
Nutanix IT personnel using Workato start building their low-code/no-code applications by documenting an optimal workflow and an optimal interactional design, said Pfeiffer.
“An optimal workflow is like how best to get dressed in the morning. You wouldn’t want to put your pants on before your underwear. Everything that IT does, especially traditional IT, needs to be tuned to be as optimal, low-cost, and performant as possible as it can be.”
Providing the ability to capture these workflows and interactions, low-code/no-code tools are at the heart of how asynchronous IT tasks — those performed by individuals on their own — have changed, according to Pfeiffer.
“Asynchronous workers aren’t that different from machines in their needs,” she said. “They need to understand the workflow, the interaction design, and the data from the operating workflow and interaction design, that reflects how things went and what worked and what didn’t.”
While ML has been around for a long time, Pfeiffer said, “it hasn’t been very accessible until we figured out a simpler way to translate our processes into it.”
Just in Time
These enablers may have arrived not a moment too soon. Nearly one-third of respondents in a recent survey of global IT professionals said they had more responsibility and longer hours on the job, with 22% also citing an increase in job-related stress. More manual IT work requires more people and a greater variety of skills unless a company can capitalize on automation.
The low-code/no-code tools being adopted at Nutanix and elsewhere are built-in, cloud-based, platform-as-a-service environments. They’re easy for non-programmers to use, with point-and-click or pull-down menu interfaces.
In a few hours, applications for administrative functions, management systems, virtual assistants, chatbots, business transactions, and many other use cases can be created. Users are able to design automated workflows that can reach into multiple systems.
Word is getting out about the simplicity, speed, and accessibility of automating processes using these tools. The low-code development platform market is expected to grow at a staggering compound annual growth rate (CAGR) of 44.2% from 2021 to 2028.